Graph Deviation Network (GDN) [1]} is a recent model aimed at anomaly detection in multivariate timeseries.
The model is trained on MTS forecasting, and anomalies are flagged when the predicted value deviates strongly from the observed value.
Since the model is essentially a forecasting method by construction, we chose to include it as a baseline in this work.
